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NAME

       v.kcv  - Randomly partition points into test/train sets.

KEYWORDS

       vector, statistics, points, point pattern

SYNOPSIS

       v.kcv
       v.kcv --help
       v.kcv map=name  [layer=string]  npartitions=integer  [column=name]   [--help]  [--verbose]
       [--quiet]  [--ui]

   Flags:
       --help
           Print usage summary

       --verbose
           Verbose module output

       --quiet
           Quiet module output

       --ui
           Force launching GUI dialog

   Parameters:
       map=name [required]
           Name of vector map
           Or data source for direct OGR access

       layer=string
           Layer number or name
           Vector features can have category values in different layers. This  number  determines
           which layer to use. When used with direct OGR access this is the layer name.
           Default: 1

       npartitions=integer [required]
           Number of partitions
           Must be > 1

       column=name
           Name for new column to which partition number is written
           Default: part

DESCRIPTION

       v.kcv randomly divides a points lists into k sets of test/train data (for npartitions-fold
       cross validation).  Test partitions are mutually exclusive. That is, a point  will  appear
       in  only  one  test  partition and k-1 training partitions.  The module generates a random
       point using the selected random number generator and then finds the closest point  to  it.
       This site is removed from the candidate list (meaning that it will not be selected for any
       other test set) and saved in the first test partition file. This is repeated until  enough
       points  have  been  selected for the test partition.  The number of points chosen for test
       partitions depends upon the number of sites available and the number of partitions  chosen
       (this  number  is  made  as  consistent  as possible while ensuring that all sites will be
       chosen for testing). This process of filling up a test partition is done k times.

NOTES

       An ideal random sites generator will follow a Poisson distribution and  will  only  be  as
       random  as  the  original  sites.  This module simply divides vector points up in a random
       manner.

       Be warned that random number generation occurs over the intervals defined by  the  current
       region of the map.

       This program may not work properly with Lat-long data.

EXAMPLES

       All examples are based on the North Carolina sample dataset.
       g.copy vect=geonames_wake,my_geonames_wake
       v.kcv map=my_geonames_wake column=part npartitions=10

       g.copy vect=geodetic_pts,my_geodetic_pts
       v.kcv map=my_geodetic_pts column=part npartitions=10

SEE ALSO

        v.random, g.region

AUTHOR

       James Darrell McCauley,
       when he was at: Agricultural Engineering Purdue University

       27 Jan 1994: fixed RAND_MAX for Solaris 2.3
       13 Sep 2000: released under GPL
       Updated to 5.7 Radim Blazek 10 / 2004
       OGR support by Martin Landa (2009)
       Speed-up by Jan Vandrol and Jan Ruzicka (2013)

       Last changed: $Date: 2014-11-28 17:22:17 +0100 (Fri, 28 Nov 2014) $

SOURCE CODE

       Available at: v.kcv source code (history)

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       © 2003-2019 GRASS Development Team, GRASS GIS 7.6.0 Reference Manual